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Member of Technical Staff - Reinforcement Learning (Simulation), AGI Autonomy Join to apply for the Member of Technical Staff - Reinforcement Learning (Simulation), AGI Autonomy role at Amazon Member of Technical Staff - Reinforcement Learning (Simulation), AGI Autonomy Join to apply for the Member of Technical Staff - Reinforcement Learning (Simulation), AGI Autonomy role at Amazon Description Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). Description Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs). Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up! Key job responsibilities Design and implement highly scalable and realistic simulation environments for training agents using reinforcement learning. Develop and deploy generative AI approaches to automate the creation of diverse and complex simulation environments and scenarios. Analyze, troubleshoot, and profile complex machine learning systems within the simulation context, identifying and resolving performance bottlenecks. Collaborate with cross-functional teams – including engineers, product managers, and scientists – to identify and solve challenging problems at the intersection of generative AI and reinforcement learning. Basic Qualifications PhD, or Master's degree or 5+ years of applied research experience Experience programming in C++, Python or related language Experience with simulation and synthetic data generation Experience with neural deep learning methods and machine learning Preferred Qualifications PhD in Computer Science, Machine Learning, or a related field 3+ years' experience building machine learning models (includes internships) Demonstrated experience in developing and implementing simulation environments or synthetic data generation for reinforcement learning. Strong programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch Excellent problem-solving skills, with the ability to think creatively and critically about complex problems Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay for this position ranges from $120,000/year in our lowest geographic market up to $350,000/year in our highest geographic market. Pay is based on a number of factors, including market location, and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit Applicants should apply via our internal or external career site. Company - Amazon.com Services LLC Job ID: A2937537 Seniority level Seniority level Not Applicable Employment type Employment type Full-time Job function Job function Research, Science, and Engineering Industries Software Development Referrals increase your chances of interviewing at Amazon by 2x Sign in to set job alerts for “Member of Technical Staff” roles. 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